1 citations · 1 across the 5 of their papers we have counts for
6 papers
Task Expansion and Cross Refinement for Open-World Conditional Modeling
Shreyas Bhat Brahmavar, Qiyang Liu, Yang Li +1
Open-world conditional modeling (OCM), requires a single model to answer arbitrary conditional queries across heterogeneous datasets, where observed variables and targets vary and…
SciDER: Scientific Data-centric End-to-end Researcher
Ke Lin, Owais Aijaz, Yilin Lu +3
While large language models accelerate scientific discovery, existing agents face severe limitations in adaptability, domain generalization, and multimodal scalability, often strug…
Information Templates: A New Paradigm for Intelligent Active Feature Acquisition
Hung-Tien Huang, Dzung Dinh, Junier B. Oliva
Active feature acquisition (AFA) is an instance-adaptive paradigm in which, at inference time, a policy sequentially chooses which features to acquire (at a cost) before predicting…
Towards Universal Neural Likelihood Inference
Shreyas Bhat Brahmavar, Yang Li, Qiyang Liu +2
We introduce universal neural likelihood inference (UNLI): enabling a single model to provide data-grounded, conditional likelihood predictions for arbitrary targets given any coll…
Dynamic Information Sub-Selection for Decision Support
Hung-Tien Huang, Maxwell Lennon, Shreyas Bhat Brahmavar +2
We introduce Dynamic Information Sub-Selection (DISS), a novel framework of AI assistance designed to enhance the performance of black-box decision-makers by tailoring their inform…
Reliable OOD Virtual Screening with Extrapolatory Pseudo-Label Matching
Yunni Qu, Bhargav Vaduri, Karthikeya Jatoth +6
Machine learning (ML) models are increasingly deployed for virtual screening in drug discovery, where the goal is to identify novel, chemically diverse scaffolds while minimizing e…